Validity of a wireless instrumented insole (WalkinSense system) for measuring gait metrics

IF 2.7 Q2 ORTHOPEDICS
Melanie Eckelt, Jennifer Fayad, Anne Backes, Gaëlle Schurmans, Frederic Garcia, Bernd Grimm, Valeria Serchi, Tobias Meyer, Thomas Solignac, Caroline Mouton, Romain Seil, Laurent Malisoux
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Abstract

Purpose

Gait analysis has become a valuable tool in assessing abnormal gait patterns and quantifying improvements resulting from interventions, particularly in the rehabilitation of orthopaedic patients. Wearables can measure gait metrics in daily life settings, but they must first be validated before being applied in such contexts. This study aims to assess the validity of a wireless instrumented insole (WalkinSense).

Methods

Recordings of 104 healthy participants were obtained at various speed and slope conditions (3 km/h, 4.5 km/h [−3°, −6°, +3° and +6°], 6 km/h and 9 km/h). Spatiotemporal and kinematic variables were collected simultaneously with an instrumented treadmill, a three-dimensional motion capture system and with the WalkinSense system. Mean bias between the systems was assessed using separate Bland–Altman analyses for each metric and condition. Mean error and limits of agreement (absolute and percentage) were calculated and the agreement was statistically quantified using a priori set thresholds (excellent <5%, good <10%, acceptable <15% and poor >15%). MAPE scores and a two-way mixed model intraclass correlation coefficient (ICC) for consistency were also calculated.

Results

All spatiotemporal variables (except double support time) showed good or excellent agreement, MAPE scores lower than 5% and ICC values > 0.88 in the walking speeds. Data collected with the WalkinSense system showed acceptable or good agreement for the spatiotemporal variables in running. Kinematic variables showed only poor agreements across all speeds and slopes.

Conclusion

These findings suggest that the WalkinSense system may be useful to quantify spatiotemporal variables with good to excellent accuracy across various walking speeds. However, based on the results of this study indicate that the WalkinSense system is not suitable for measuring kinematic variables without substantial improvements.

Level of Evidence

Level II, diagnostic studies.

Abstract Image

无线仪表鞋垫(WalkinSense系统)测量步态指标的有效性
目的步态分析已成为评估异常步态模式和量化干预所带来的改善的有价值的工具,特别是在骨科患者的康复中。可穿戴设备可以在日常生活环境中测量步态指标,但在应用于此类环境之前,必须先对其进行验证。本研究旨在评估无线仪器鞋垫(WalkinSense)的有效性。方法采集104名健康受试者在不同速度和坡度条件下(3 km/h、4.5 km/h[−3°、−6°、+3°和+6°]、6 km/h和9 km/h)的记录。时空和运动变量通过仪器跑步机、三维运动捕捉系统和WalkinSense系统同时收集。对每个指标和条件使用单独的Bland-Altman分析来评估系统之间的平均偏倚。计算平均误差和一致性限度(绝对和百分比),并使用先验设置阈值(优秀5%,良好10%,可接受15%和差15%)对一致性进行统计量化。还计算了MAPE分数和用于一致性的双向混合模型类内相关系数(ICC)。结果所有时空变量(除双支撑时间外)均表现出良好或极好的一致性,步行速度的MAPE得分低于5%,ICC值>; 0.88。WalkinSense系统收集的数据显示,在运行过程中,时空变量的一致性可以接受或很好。运动学变量在所有速度和坡度上的一致性很差。研究结果表明,WalkinSense系统可用于在不同步行速度下量化时空变量,并具有良好的准确性。然而,基于本研究的结果表明,如果没有实质性的改进,WalkinSense系统不适合测量运动变量。证据等级II级,诊断性研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Experimental Orthopaedics
Journal of Experimental Orthopaedics Medicine-Orthopedics and Sports Medicine
CiteScore
3.20
自引率
5.60%
发文量
114
审稿时长
13 weeks
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